Carolyn Parnell on Big Data at MHTA
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Transcript of Carolyn Parnell on Big Data at MHTA
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INFORMATION TECHNOLOGY FOR MINNESOTA GOVERNMENT
4/25/2012
Big Data and the State of Minnesota
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Immature space for state government
As with many new areas, government is slower to move
Lagging behind private sector in terms of investment
Big Data in MN State
Government
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We are “data rich, but information poor”
Large number of state systems
Large volume of data
Systems are aligned to specific functions, data
Efforts have been made to leverage data within systems to drive value for citizens and better government (Business analytics, Unemployment Insurance system)
Big Data in MN State
Government
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Next Step: Begin to aggregate data from multiple systems
Have looked at data within systems, now must bring that data together in a way that creates value
This is where HUGE potential lies, holy grail of Big Data in government
Example: Aligning data from DNR, MnDOT and DEED to assess impact of transportation projects on recreational activity and tourism during MN summer
Frontiers for Big Data in
MN
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Challenge 1: Technical barriers, new data processes, data alignment. (Similar to private sector)
Challenge 2: Stewardship and storage of data, state and federal regulations, data restrictions, data ownership (not similar to private sector)
Tension: Must not neglect responsibilities as “stewards” of public data in effort to overcome technical challenges of Big Data
Challenges for Government
in Big Data
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There is potential to use Big Data for:
Human Resources: tying internal workforce data to outcomes, analyzing business processes, providing integrated services
Public Services: Crime prevention (Memphis PD uses multi-layered crime analysis of “hot spots” based on crime data to allocate resources)
Citizen Outreach/Empowerment: Boston’s “Adopt-a-Hydrant” program uses geographic data to empower citizens to clear hydrants after snowstorms
Where We Go from Here
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Business IntelligenceRFP was issued in April 2011 for use of data analytics to reduce waste, fraud and abuse in state programs and agencies in 9 categories including:
Fleet Management Building Efficiency Medicaid Fraud and
Investigation Tax Fraud and
Investigation
Current Big Data Efforts
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Statewide Longitudinal Data System
MN awarded $12.4 million in 2010 for the design and implementation of a statewide longitudinal data system
Examine student progress from early childhood through K12, higher education and into careers
Transition Minnesota’s education data capacity to a fully interoperable, enterprise-level data collection, reporting and analysis system
Includes data sharing connections across multiple state agencies
Current Big Data Efforts
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Impact of IT consolidation for citizens
Chief Analytics Officer/Chief Data Officer
Next Steps